Reprinted from: LA PRENSA newspaper
Date: 26 October 1986
Satellite Imagery for Crop Forecasts
The advance knowledge of the planted areas, yields and grain production through satellite imagery is now one of the fundamental tools for the international marketing of these products. About this exciting topic we talked with Agrcicultural Engineer Carlos M. Viola, Vicepresident of Aeroterra SA.
In the dialogue that we had with him, he explains that Earth satellite Corporation, a North American company, developed in the early 70s, the “Agricultural Cropcast Information System”. This system, says Mr. Viola, was born out of the need to obtain forecasts of production in those countries where data collection systems are obsolete, slow, inaccurate or not available.
Our company Aeroterra SA, he adds, was established in 1973 and is dedicated to the comprehensive assessment of natural resources by conventional and satellite remote sensing techniques and is the exclusive representative for Argentina, Uruguay and Paraguay of Earth Satellite Corporation.
Now explaining the Cropcast System, Mr. Viola says that it is totally different from other models in that it uses agricultural and meteorological information from weather satellites and ground stations in order to obtain a continuous spatial and temporal description of the changes that affect plants.
Uses computerized information, combining the political, physical, and historical data with dynamic statistical models to obtain estimates of planted areas, production and yields at provincial level.
The main objective of the system is to provide real-time information, says Mr. Viola. The crop production forecasts are available between two weeks to two months before the reports of the United States Department of Agriculture (USDA).
Cropcast uses, combines and processes: 1) Information obtained by meteorological and natural resources satellites, 2) Data from meteorological land stations that are part of the global meteorological network, 3) advanced computer techniques; 4) Historical information of each crop in each area, 5) advanced statistical models for each crop and its environment. Furthermore, the system can incorporate data obtained in the field or by local reconnaissance aircraft.
Cropcast provides information on Argentina, West Africa, Australia, Brazil, Canada, China, USA, Europe, Philippines, India, Pakistan, Paraguay, South Africa, Soviet Union, New Zealand on the following crops: spring and winter wheat, corn, sorghum, barley, oats, sunflower, soybean, peanut, rapeseed, cotton, sugarcane, sugarbeet, coffee and cocoa.
Regarding this issue, Mr. Viola says that in 1975 verification tests were conducted and the Cropcast results were compared with results obtained by traditional methods and published by the USDA. These tests were performed for spring wheat in the states of Montana, South Dakota, North Dakota and Minnesota and reported a 97.7% accuracy for the information obtained two months before harvest and 99.2% for that obtained at the time of harvest.
There are also results for our country. In January 1979 Cropcast forecasted data for soybeans in Argentina. Yield was estimated at 2100 kilograms per hectare, a planted area of 1.8 million hectares and a production of 3.8 million tons. Nine months later, in early October official data released showed a yield of 2313 kilograms per hectare, planted area of 1.6 million hectares and a production of 3.7 million tons.
Mr. Viola notes that the system is accessible and extremely useful for government and private agencies related to agriculture and trade policy. Also for brokers, traders, exporters, food and fiber processors, manufacturers of chemicals, agricultural machinery, seed companies, cooperatives and others.
At the end of our dialogue Mr. Viola reflects on the value of advance information, saying that it may be the key tool for good business. The global grain trade annually involves billions of dollars and gains and losses of those who participate in it mainly depend on the information that they possess in a timely manner regarding global harvests.